Topological side-chain classification of β-turns: Ideal motifs for peptidomimetic development

Summary

β-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of β-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. β-turns have traditionally been classified into various types based on the backbone dihedral angles (φ2, ψ2, φ3 and ψ3). Indeed, 57–68% of β-turns are currently classified into 8 different backbone families (Type I, Type II, Type I′, Type II′, Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified β-turns). Although this classification of β-turns has been useful, the resulting β-turn types are not ideal for the design of β-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted β-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C_α–C_β vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C_α–C_β vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of β-turns. The mean structures of the nine clusters are useful for the development of β-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.